Image Identification Computer Vision Model
85 Total Images
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Dataset Split
Train Set 88%
75Images
Valid Set 8%
7Images
Test Set 4%
3Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
Shear: ±10° Horizontal, ±10° Vertical
Grayscale: Apply to 15% of images
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 1.2px
Noise: Up to 1.76% of pixels